Dual Model Architecture: Practical Experience in AI Agent Development

This article shares the author’s practical experience in developing AI Agents. Initially attempting to implement conversational functionality using Spring AI, the author encountered numerous technical challenges. The approach then shifted to the LangChain framework, adopting a dual model architecture design: one model handles supervision, reflection, and retries, while another model handles the actual work. Concurrently, the author developed supporting business tools to form a complete solution. This practical experience offers valuable reference for AI Agent developers, particularly in technology selection and architecture design.